In recent years, with the spread of an information-processing apparatus and the development of a communication network, an amount of information that the information-processing apparatus can turn into a target of processing has become enormous. The information that the information-processing apparatus can turn into a target of processing is roughly classified into two types of information, namely, structured information and unstructured information. The structured information includes numerical information such as time-series data, text information classified for every item, or the like. The unstructured information includes text information that is not classified for every item, an image, a voice, or the like. Conventionally, it was difficult to turn the unstructured information into a target of processing as compared with the structured information. However, with the development of a data-mining technique, it has gradually come to be able to turn the same into a target of processing.
The structured information such as the time-series data, unlike the unstructured information, can be represented by a graph, a table, or the like. For this reason, it is often the case that the structured information is more suitable to intuitively understand a change of a value or the like than the unstructured information. Meanwhile, since the structured information only represents a quantitative fact, it is difficult to grasp a fact from the structured information. For example, in the time-series data of a stock price, even if a decline in stock price is observed, the reason cannot be grasped. The structured information may be insufficient for understanding the background fact for this reason, and therefore, the unstructured information, for example, data of newspaper articles or the like is required.